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experiments Relevant experimental method development Surface characterisation, optical and visual characterisation Data analysis Complete the doctoral education until obtaining a doctorate Contribution to
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contribute to the current teaching needs of the Faculty of Law, including the multidisciplinary master program in human rights . The purpose of the fellowship is research training leading to the successful
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methodological capacities as well as documented expertise in computational methods. Experience with high performance computing is strongly preferred. Experience from applied work in change and anomaly detection is
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development of computer systems for data analysis, development of machine learning methods, and the clinical use of technology. Within the research groups you will therefore work together with computer
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in-depth qualitative analyses but also mixed-methods approaches, possibly enabled by emerging AI-enhanced techniques. The PhD project should overall contribute to a better understanding collaborative
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level subject/master’s degree worth 120 ECTS in health sciences, kinesiology, or similar excellent working knowledge at master’s degree level of quantitative research methods and statistics experience
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-prediction benchmark studies. Depending on the qualifications and preferences of the candidate, the work may entail experimental investigations and/or modelling in the open-source computational fluid dynamics
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employment period is three years. A premise for employment is that the PhD Research Fellow will be enrolled in USN's PhD-program in Technology within three months after accession. About the PhD-project
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in the open-source computational fluid dynamics (CFD) code PDRFOAM. The work will be conducted in collaboration with other research projects on hydrogen safety at the department. The position offers a